Credit decisions, risk signals, fraud indicators, consumer expectations, and dispute volumes are all moving faster than the traditional monthly reporting cycle. More timely credit data can help lenders identify changes sooner, strengthen fraud detection and portfolio risk management, and better reflect key consumer credit events in a way that aligns with expectations for more current, accurate financial information.
Join CDIA for this complimentary webinar to hear directly from financial institutions and the credit reporting agencies on why more frequent reporting matters, how the industry is preparing, and where fresher data can deliver meaningful value across the credit lifecycle.
What you’ll hear:
- Perspectives from financial institutions on the risk management, fraud prevention, operational, and customer experience benefits of more timely credit data
- CRA perspectives on readiness to support more frequent reporting
- Practical insights on how fresher data may support better decisioning, stronger portfolio visibility, earlier fraud and identity risk detection, dispute reduction, and improved data quality
- Business use cases for reporting key credit events closer to when they occur, including originations, payoffs, high balance changes, account closures, and other material account events
Moderator:
- Dan Smith, President and CEO, CDIA
Speakers include:
- Brian Campbell, VP, Data Operations Management & Consulting, Experian
- Michelle Simms, SVP, Business Execution Director, Furnishings Leader, CBL Chief Administration Office, Wells Fargo
- Jim Utz, Vice President, Data Integration, TransUnion
- Jeff Van Schoyck, Director, Data Management Services, Innovis
- Darin Wharton, Manager, Global Data Contributor Services Group, Equifax
Whether your institution already reports selected account events outside the normal reporting cycle or is evaluating future opportunities, this discussion will explore practical business use cases, lessons learned, and emerging industry perspectives on the value of more timely credit data.
